With hand-held digital capture devices becoming pervasive in modern society, more and varied uses for them become apparent. The ability to capture an image of a printed document with one's cell phone or digital camera and have that image converted into useful data such as text is highly desirable and has many applications. The traditional means of converting a printed document into textual information usually requires the use of a document scanner and an optical character recognition (OCR) system. The quality of the images produced by document scanners is typically excellent and the OCR process on these types of images is generally very good, although not always perfect. In general, the better the quality level of images provided to the OCR process, the better the textual output generated will be.
While images of documents captured by a cell phone or digital camera are convenient, they are generally inferior in quality to images generated using document scans. Various factors such as lens system aberrations, camera position, camera movement and lighting uniformity and brightness, contribute to the poorer image quality images. Because of the inferior image quality level, these images typically produce unacceptable results when an OCR process is used to extract textual information.
A number of methods have been proposed for improving OCR output. However, these methods are inefficient and insufficient to provide adequate results for images of documents captured using hand-held digital imaging devices.
U.S. Pat. No. 5,519,786 to Courtney et al., entitled “Method and apparatus for implementing a weighted voting scheme for multiple optical character recognition systems,” describes a method that involves processing an input file using a plurality of different OCR processors. For a particular character in the document, the characters reported by each OCR processor are grouped into a set of character candidates. For each character candidate, a weight is generated in accordance with a confusion matrix which stores probabilities of a particular OCR to identify characters accurately. The weights are then compared to determine which character candidate to output.
U.S. Pat. No. 5,805,747 to Bradford, entitled “Apparatus and method for OCR character and confidence determination using multiple OCR devices,” describes another method which uses a plurality OCR processors. Each of different OCR processors outputs recognized characters along with the OCR processor's own determination of how confident it is in the identification of the correct characters. The OCR system uses that data output from each of the different OCR processors along, with other attributes of the indicated character to produce a combined confidence indication.
U.S. Pat. No. 7,734,092 to Curtis et al., entitled “Multiple image input for optical character recognition processing systems and methods,” describes a method for selecting processing a captured image through a plurality of binarization and OCR processes to provide corresponding OCR output files, and selecting between the resulting OCR output files based on associated metrics.
While some of the foregoing methods can provide somewhat improved results, there remains a need to provide better results with a more practical solution.